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PAHO/PAHEF WORKSHOP EDUCATION FOR CHILDHOOD OBESITY PREVENTION: A LIFE-COURSE APPROACH Aruba, June 2012. Choice of study design: randomized and non-randomized approaches. Iná S. Santos Federal University of Pelotas Brazil. Outline of the presentation. Introduction Types of evidence

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Choice of study design randomized and non randomized approaches

PAHO/PAHEF WORKSHOP EDUCATION FOR CHILDHOOD OBESITY PREVENTION: A LIFE-COURSE APPROACHAruba, June 2012

Choice of study design: randomized and non-randomized approaches

Iná S. Santos

Federal University of Pelotas

Brazil


Outline of the presentation
Outline of the presentation

  • Introduction

    • Types of evidence

    • Internal and external validity

  • Randomized controlled trials

  • Non-randomized designs

  • Victora et al. Evidence-based Public Health: moving beyond randomized trials. Am J Public Health 2004;94(3):400-405

  • Habicht JP et al. Evaluation designs for adequacy, plausibility and probability of public health programme performance and impact. Intern J Epidemiology 1999;28:10-18


Part i
Part I

  • Introduction

    • Types of evidence

    • Internal and external validity



Valididy internal and external
Valididy: internal and external

External population

Target population

Actual population

Sample


Validity
Validity

  • Internal validity

    • Are the study results true for the target population?

    • Are there errors that affect the study findings?

      • Systematic error (bias, confounding)

      • Random error (precision)

  • External validity

    • Generalizability

    • Are the study results applicable to other settings?


Validity1
Validity

  • Internal validity

    • May be judged on the basis of the study methods

  • External validity

    • Require a “value judgment”


Part ii
Part II

Randomized controlled trials

(RCTs)


Internal validity in probability studies
Internal validity in probability studies

RCTs are the gold standard for internal validity


Rct from cochrane collaboration
RCT (from Cochrane Collaboration)

  • In a RCT participants are assigned by chance to receive either an experimental or control treatment.

  • When a RCT is done properly, the effect of a treatment can be studied in groups of people who are the same at the outset, and treated in the same way, except for the intervention being studied.

  • Any differences then seen in the groups at the end of the trial can be attributed to the difference in treatment alone, and not to bias or chance.


Randomised controlled trials
Randomised controlled trials

  • Prioritise internal validity

    • random allocation reduces selection bias and confounding

    • blinding reduces information bias

  • Gained popularity through clinical trials of new drugs

  • Essential for determining efficacy of new biological agents

  • Adequate for short causal chains

    • biological effects of drugs, vaccines, nutritional supplements, etc.

drug  pharmacological reaction disease cure or alleviation


Pooling data from rcts
Pooling data from RCTs

  • Systematic review

    • Comprehensive search for all high-quality scientific studies on a specific subject

      • E.g. on effects of a drug, vaccine, surgical technique, behavioral intervention, etc

  • Meta-analysis

    • Groups data from different studies to determine an average effect

    • Improves the precision of the available estimates by including a greater number of people

    • But: data from different studies cannot always be combined


What does a rct show

The probability that the observed result is due to the intervention

But additional evidence is required to make this result conceptually plausible

Biological plausibility

Operational plausibility

What does a RCT show?


Special issues in rcts
Special issues in RCTs intervention

  • “Intent-to-treat” analyses

    • Individuals/groups should remain in the group to which they were originally assigned

  • Units of analyses

    • It is incorrect to use group allocation (e.g., health centers, communities, etc) and to analyse the data at individual level

    • This has implications for sample size calculation and for analysis methods


Consort statement
CONSORT Statement intervention

  • Allocation

  • Rationale

  • Eligibility

  • Interventions

  • Objectives

  • Outcomes

  • Sample size

  • Randomization

    • Sequence generation

    • Concealment

    • Implementation

    • Blinding (masking)

  • Statistical methods

  • Participant flow

  • Recruitment

  • Baseline data

  • Numbers analyzed

  • Outcomes and estimation

  • Ancillary analyses

  • Adverse events

  • Interpretation

  • Generalizability

  • Overall evidence


Major steps in public health trials
Major steps in Public Health trials intervention

  • Central-level provision of intervention to local outlets (e.g. health facilities)

  • Local providers’ compliance with delivery of intervention

  • Recipient compliance with intervention

  • Biological effect of intervention

Source: Victora, Habicht, Bryce, AJPH 2004


Example of public health intervention nutrition counselling trial

Central team intervention

is competent

HWs are

trainable

Equipment is

available

Utilization

is adequate

Food is

available

Lack of food

is a cause of

malnutrition

Example of Public Health Intervention: Nutrition Counselling Trial

National programme is implemented

Health workers are trained

HW knowledge increases

HW performance improves

Maternal knowledge increases

Child diets change

Energy intake increases

Nutritional status improves

Source: Santos, Victora et al. J Nutr 2001


Example of public health intervention nutrition counselling trial1
Example of Public Health Intervention: interventionNutrition Counselling Trial

National programme is implemented

Health workers are trained

HW knowledge increases

0.807=0.21

HW performance improves

Maternal knowledge increases

Child diets change

Energy intake increases

Nutritional status improves

Source: Santos, Victora et al. J Nutr 2001


Are rct findings generalizable to routine programmes

The dose of the intervention may be smaller intervention

behavioural effect modification

provider behaviour

recipient behaviour

The dose-response relationship may be different

biological effect modification

Are RCT findings generalizable to routine programmes?

The longer the causal chain, the more likely is effect modification

Source: Victora, Habicht, Bryce, AJPH 2004


Curvilinear associations
Curvilinear associations intervention

Trials often

done here

Results often

applied here

Source: Victora, Habicht, Bryce, AJPH 2004


Why do rcts have a limited role in large scale effectiveness evaluations
Why do RCTs have a limited role in large-scale effectiveness evaluations

  • Often impossible to randomize

    • unethical, politically unacceptable, rapid scaling up

  • Evaluation team affects service delivery

    • service delivery is at least “best-practice”

  • Effect modification is the rule

    • are meta-analyses of complex programmes meaningful?

    • need for local data

  • Need for supplementary approaches for evaluations in Public Health


Part iii
Part III evaluations

Non-randomized designs

(Quasi-experiments)


Types of inference in impact evaluations
Types of inference in impact evaluations evaluations

  • Adequacy (descriptive studies)

    • the expected changes are taking place

  • Plausibility (observational studies)

    • observed changes seem to be due to the programme

  • Probability (RCTs)

    • randomised trial shows that the programme has a statistically significant impact

Source: Habicht, Victora, Vaughan, IJE 1999



Adequacy evaluations
Adequacy evaluations studies

  • Questions:

    • Were the initial goals achieved?

      • E.g.: reduce underfive mortality by 20%

    • Were the observed trends in impact indicators

      • in the expected direction?

      • of adequate magnitude?


Plausibility evaluations
Plausibility evaluations studies

  • Question:

    • Is the observed impact likely due to the intervention?

  • Require ruling out influence of external factors:

    • need for comparison group

    • adjustment for confounders

  • Also known as quasi-experiments


Adequacy plausibility designs 1
Adequacy/plausibility designs (1) studies

  • Design: cross-sectional

  • Measurement points: once

  • Outcome: difference or ratio

  • Control group:

    • Individuals who did not receive the intervention

    • Groups/areas without the intervention

    • Dose-response analyses, if possible


Ort and diarrhea deaths in brazil
ORT and diarrhea deaths in Brazil studies

Each dot = 1 state

Spearman r=-0,61 (p=0,04)


Adequacy plausibility designs 2
Adequacy/plausibility designs (2) studies

  • Design: longitudinal (before-and-after)

  • Measurement points: twice or more

  • Outcome: change

  • Control group:

    • The same or similar individuals, before the intervention

    • The same groups/areas, before the intervention

    • Time-trend analyses, if possible


Hib vaccine in uruguay
Hib vaccine in Uruguay studies

In Uruguay, reported Hib cases declined by over 95 percent after the introduction of routine infant Hib immunisation in 1994.

Source: PAHO, 2004


Adequacy plausibility designs 3
Adequacy/plausibility designs (3) studies

  • Design: longitudinal-control

  • Measurement points: twice or more

  • Outcome: relative change

  • Control group:

    • The same or similar individuals, before the intervention

    • The same groups/areas, before the intervention

    • Time-trend analyses, if possible


Adequacy plausibility designs 4
Adequacy/plausibility designs (4) studies

  • Design: case-control

  • Measurement points: once

  • Comparison: exposure to intervention

  • Groups:

    • Cases: individuals with the disease of interest

    • Controls: sample of the population from which cases originated


Stunting in Tanzania studies

Stunting prevalence among children aged 24-59 months

p (mean haz)

= 0.05

Source: Schellenberg J et al


Source: Des Jarlais, Lyles, Crepaz and the TREND Group, AJPH 2004


Conclusions 1
Conclusions Designs (TREND) (1)

  • RCTs are essential for

    • clinical studies

    • community studies for establishing the efficacy of relatively simple interventions

  • RCTs require additional evidence from non-randomised studies for increasing their external validity


Conclusions 2
Conclusions Designs (TREND) (2)

  • Given the complexity of many Public Health interventions, adequacy and plausibility studies are essential in different populations

    • even for interventions proven by RCTs

  • Adequacy evaluations should become part of the routine of decision-makers

    • and plausibility evaluations too, when possible


THANK YOU Designs (TREND)


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